# Brand Mention Monitor — Hacker News + Google News (`abidchaudhry/brand-mention-monitor`) Actor Watch Hacker News and Google News for your brand, product, or competitor keywords. Keyless, dedupes across scheduled runs — perfect for a daily alert pipeline. - **URL**: https://apify.com/abidchaudhry/brand-mention-monitor.md - **Developed by:** [Abid Chaudhry](https://apify.com/abidchaudhry) (community) - **Categories:** Marketing, News, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Brand Mention Monitor — Hacker News + Google News Know when the internet talks about you. This actor sweeps **Hacker News (stories *and* comments)** and **Google News** for your keywords and outputs clean, deduplicated mention records — built to run on a schedule as a free-tier replacement for Mention, Brand24, or Google Alerts (which famously misses most of HN). ### Why this one - **Keyless** — no API keys, no OAuth, nothing to configure but your keywords. - **Dedupes across runs** — it remembers what it already reported, so a daily schedule yields only *new* mentions. No more re-reading the same thread. - **HN comments included** — most brand chatter on HN happens in comment threads, not story titles. Tools that only search titles miss it. - **Automation-ready output** — pipe the dataset into Slack, email, Telegram, a Google Sheet, or your own triage workflow via Apify integrations. ### Input ```json { "keywords": ["Acme Corp", "acme.dev", "Jane Doe"], "sources": ["hackernews", "googlenews"], "lookbackHours": 24 } ```` Track competitors too — mentions are tagged with the keyword that matched, so one run can watch your whole market. ### Output (one dataset item per mention) ```json { "source": "hackernews", "kind": "comment", "keyword": "acme.dev", "title": "We switched from Acme to self-hosting and cut costs 80%...", "url": "https://news.ycombinator.com/item?id=41234567", "externalUrl": null, "author": "throwaway2026", "points": null, "numComments": null, "publishedAt": "2026-07-05T14:03:11.000Z" } ``` ### Recommended setup 1. Create a **Schedule** in Apify: daily at your morning time, with `lookbackHours: 25` (small overlap; dedup removes the seam). 2. Add an **integration** on the actor: Slack message, email, or webhook per run with new items. 3. Add your competitors' names as keywords — the `keyword` field tells you who each mention is about. ### FAQ **Which sources exactly?** Hacker News via the official Algolia search API (stories + comments), Google News via its public RSS feed (respects your language/country settings). **Does it dedupe between HN and Google News?** URLs are normalized (tracking params stripped) and deduped globally per run and across runs. **Rate limits?** Both sources are polite-use public endpoints; the default 50 items/keyword/source keeps you well inside them. # Actor input Schema ## `keywords` (type: `array`): Brand names, product names, domains, founder names, competitors — each is searched independently. ## `sources` (type: `array`): Where to look for mentions. ## `lookbackHours` (type: `integer`): Only include items published within this window. Match it to your run schedule (24 for daily, 168 for weekly). ## `language` (type: `string`): Two-letter language code. ## `country` (type: `string`): Two-letter country code. ## `maxItemsPerKeyword` (type: `integer`): Upper bound on results per keyword per source per run. ## `dedupeAcrossRuns` (type: `boolean`): Remember previously seen URLs so scheduled runs only output NEW mentions. Disable for one-off full sweeps. ## Actor input object example ```json { "keywords": [ "OpenAI", "anthropic.com" ], "sources": [ "hackernews", "googlenews" ], "lookbackHours": 24, "language": "en", "country": "US", "maxItemsPerKeyword": 50, "dedupeAcrossRuns": true } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "keywords": [ "OpenAI", "anthropic.com" ] }; // Run the Actor and wait for it to finish const run = await client.actor("abidchaudhry/brand-mention-monitor").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "keywords": [ "OpenAI", "anthropic.com", ] } # Run the Actor and wait for it to finish run = client.actor("abidchaudhry/brand-mention-monitor").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "keywords": [ "OpenAI", "anthropic.com" ] }' | apify call abidchaudhry/brand-mention-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=abidchaudhry/brand-mention-monitor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Brand Mention Monitor — Hacker News + Google News", "description": "Watch Hacker News and Google News for your brand, product, or competitor keywords. Keyless, dedupes across scheduled runs — perfect for a daily alert pipeline.", "version": "0.1", "x-build-id": "IxhJB5fnPCSYCobAa" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/abidchaudhry~brand-mention-monitor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-abidchaudhry-brand-mention-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/abidchaudhry~brand-mention-monitor/runs": { "post": { "operationId": "runs-sync-abidchaudhry-brand-mention-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/abidchaudhry~brand-mention-monitor/run-sync": { "post": { "operationId": "run-sync-abidchaudhry-brand-mention-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "keywords" ], "properties": { "keywords": { "title": "Keywords", "type": "array", "description": "Brand names, product names, domains, founder names, competitors — each is searched independently.", "items": { "type": "string" } }, "sources": { "title": "Sources", "type": "array", "description": "Where to look for mentions.", "items": { "type": "string", "enum": [ "hackernews", "googlenews" ], "enumTitles": [ "Hacker News (stories + comments)", "Google News (articles)" ] }, "default": [ "hackernews", "googlenews" ] }, "lookbackHours": { "title": "Lookback window (hours)", "minimum": 1, "maximum": 720, "type": "integer", "description": "Only include items published within this window. Match it to your run schedule (24 for daily, 168 for weekly).", "default": 24 }, "language": { "title": "Language (Google News)", "type": "string", "description": "Two-letter language code.", "default": "en" }, "country": { "title": "Country (Google News)", "type": "string", "description": "Two-letter country code.", "default": "US" }, "maxItemsPerKeyword": { "title": "Max items per keyword per source", "minimum": 1, "maximum": 100, "type": "integer", "description": "Upper bound on results per keyword per source per run.", "default": 50 }, "dedupeAcrossRuns": { "title": "Dedupe across runs", "type": "boolean", "description": "Remember previously seen URLs so scheduled runs only output NEW mentions. Disable for one-off full sweeps.", "default": true } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```